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Updated: Feb 25, 2026

Simultaneous Measurement of Turbulence and Particle Kinematics Using Flow Imaging Techniques

Simultaneous Measurement of Turbulence and Particle Kinematics Using Flow Imaging Techniques

Published on: March 12, 2019

Enhanced particle-filtering framework for vessel segmentation and tracking.

Sang-Hoon Lee¹, Jiwoo Kang¹, Sanghoon Lee¹

¹Department of Electrical and Electronic Engineering, Yonsei University, Seoul, 120-749, Republic of Korea.

Computer Methods and Programs in Biomedicine

|August 5, 2017

Summary

This summary is machine-generated.

A new particle-filtering method enhances vessel segmentation and tracking for detecting anomalies. This approach improves accuracy and addresses common particle filter challenges, aiding in 3D vessel analysis.

Keywords:

Level set method Particle filter Vessel segmentation Vessel tracking

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Area of Science:

Medical Imaging
Computational Biology

Background:

Accurate vessel segmentation and tracking are crucial for detecting anomalies.
Existing methods face challenges in robustness and accuracy.

Purpose of the Study:

To propose a robust vessel segmentation and tracking method.
To address the demand for detecting and tracking vessel anomalies.

Main Methods:

Utilized the level set method for vessel boundary segmentation.
Employed a particle filter for tracking boundary variations between slices.
Enhanced performance through localized importance density and a novel weighting policy to mitigate degeneracy and sample impoverishment.

Main Results:

The proposed algorithm outperformed conventional methods in segmentation and tracking.
The novel weighting policy effectively suppressed degeneracy and sample impoverishment.
Achieved higher tracking accuracy compared to existing techniques.

Conclusions:

The developed method offers improved 3D vessel tracking and rendering capabilities.
Expected to be valuable for applications requiring precise vessel analysis.